Comment by sanderjd
1 day ago
I don't think it's "on top"? I think it's an expert system where (at least) one of the experts is an LLM, but it doesn't have to be LLMs from bottom to top.
1 day ago
I don't think it's "on top"? I think it's an expert system where (at least) one of the experts is an LLM, but it doesn't have to be LLMs from bottom to top.
On the side, under, wherever. The point is, this is just re-inventing past failed attempts at AI.
Except past attempts didn't have the ability to pass on to modern foundation models.
Look, I dunno if this idea makes sense, it's why I posed it as a question rather than a conviction. But I broadly have a sense that when a new technology hits, people are like "let's use it for everything!", and then as it matures, people find more success in interesting it with current approaches, or even trying older ideas but within the context of the new technology.
And it just strikes me that this "routing to tools" thing looks a lot like the part of expert systems that did work pretty well. But now we have the capability to make those tools themselves significantly smarter.
Expert systems are not the problem per se.
The problem is that AI is very often a way of hyping software. "This is a smart product. It is intelligent". It implies lightning in a bottle, a silver bullet. A new things that solves all your problems. But that is never true.
To create useful new stuff, to innovate, in a word, we need domain expertise and a lot of work. The world is full of complex systems and there are no short cuts. Well, there are, but there is always a trade off. You can pass it on (externalities) or you can hide (dishonesty) or you can use a sleight of hand and pretend the upside is so good, it's magical so just don't think about what it costs, ok? But it always costs something.
The promise of "expert systems" back then was creating "AI". It didn't happen. And there was an "AI winter" because people wised up to that shtick.
But then "big data" and "machine learning" collided in a big way. Transformers, "attention is all you need" and then ChatGPT. People got this warm fuzzy feeling inside. These chatbots got impressive, and improved fast! It was quite amazing. It got A LOT of attention and has been driving a lot of investment. It's everywhere now, but it's becoming clear it is falling very short of "AI" once again. The promised land turned out once again to just be someone else's land.
So when people look at this attempt at AI and its limitations, and start wondering "hey what if we did X" and X sounds just like what people were trying when we last thought AI might just be around the corner... Well let's just say I am having a deja vu.
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